[Poor prognostic factors in patients hospitalized for COVID-19].

BACKGROUND: The clinical spectrum of COVID-19 varies from no or mild symptoms to pneumonia with fatal complications. The aim of the study was to find predictors of mortality and admission in the intensive care unit (ICU) in patients hospitalized for COVID-19. METHODS: Retrospective study of a cohort of patients admitted for COVID-19 between March 2020 and February 2021. Demographic, clinical, radiological and laboratory variables were described at admission. Independent predictors of mortality and ICU admission were identified by means of backward stepwise logistic regression and described in terms of odds ratio (OR) and 95% confidence interval (95%CI). RESULTS: A total of 883 patients were included, 51.8% men with a mean age of 68; 1.8% readmissions. 17.6% of patients died (n=154). The independent predictors of mortality were age (OR=1.071; 95%CI: 1.046-1.095), percentage of oxygen saturation (SatO2) (OR=0.938; 95%CI: 0.903-0.974), diastolic blood pressure (DBP, OR= 0.972; 95%CI: 0.955-0.989), creatinine (OR=1.516; 95%CI: 1.088-2.113), INR (OR=1.199; 95%CI: 1.012-1.419) and sodium (OR=1.082; 95%CI: 1.037-1.128). Eight percent of patients were admitted to ICU; the independent predictors were: male sex (OR=2.079; 95%CI: 1.099-3.935), age (OR=0.960; 95%CI: 0.942-0.979), SatO2 (OR=0.925; 95%CI: 0.889-0.962), creatinine (OR=1.551; 95%CI: 1.118-2.152) and C-reactive protein (CRP, OR=1.003; 95%CI: 1.000-1.007). CONCLUSION: The identification of independent predictors of mortality (age, SatO2, DBP, creatinine, INR, sodium) and ICU admission (sex, age, SatO2, creatinine, and CRP) allowed for the stratification of patients to adapt clinical care protocols to these findings, thereby improving medical decisions.

Factores de mal pronóstico en pacientes hospitalizados por COVID-19 / Poor prognostic factors in patients hospitalized for COVID-19

Fundamento: El espectro clínico de la COVID-19 varía entre sintomatología leve o ausente hasta neumonías con complicaciones mortales. El objetivo del estudio fue determinar los factores predictivos de mortalidad e ingreso en cuidados intensivos (UCI) en pacientes hospitalizados por COVID-19. Metodología: Estudio retrospectivo de una cohorte de pacientes ingresados por COVID-19 entre marzo de 2020 y febrero de 2021. Se describieron las variables demográficas, clínicas, radiológicas y analíticas al ingreso. Los predictores independientes de mortalidad e ingreso en UCI se identificaron mediante regresión logística por pasos hacia atrás y se describieron como odds ratio (OR) e intervalo de confianza al 95% (IC95%). Resultados: Se incluyeron 883 pacientes, 51,8% varones y edad media 68 años; el 1,8% reingresó. Fallecieron 154 pacientes (17,6%); los predictores independientes de mortalidad fueron: edad (OR=1,071; IC95%: 1,046-1,095), porcentaje de saturación de oxígeno (SatO2) (OR=0,938; IC95%: 0,903-0,974), tensión arterial diastólica (PAD, OR=0,972; IC95%: 0,955-0,989), creatinina (OR=1,516; IC95%: 1,088-2,113), INR (OR=1,199; IC95%: 1,012-1,419) y sodio (OR=1,082; IC95%: 1,037-1,128). El 8% de los pacientes ingresaron en UCI; las variables predictoras independientes fueron: sexo masculino (OR=2,079; IC95%: 1,099-3,935), edad (OR=0,960; IC95%: 0,942-0,979), SatO2 (OR=0,925; IC95%: 0,889-0,962), creatinina (OR=1,551; IC95%: 1,118-2,152) y proteína C reactiva (PCR, OR=1,003; IC95%: 1,000-1,007). Conclusiones: La identificación de predictores independientes de mortalidad (edad, SatO2, PAD, creatinina, INR, sodio) y de ingreso en UCI (sexo, edad, SatO2, creatinina y PCR) permite estratificar a los pacientes y adaptar los protocolos de atención clínica a estos hallazgos, mejorando las decisiones médicas.(AU)

Background: The clinical spectrum of COVID-19 varies from no or mild symptoms to pneumonia with fatal complications. The aim of the study was to find predictors of mortality and admis-sion in the intensive care unit (ICU) in patients hospitalized for COVID-19. Methods: Retrospective study of a cohort of patients admitted for COVID-19 between March 2020 and February 2021. Demographic, clinical, radiological and laboratory variables were described at admission. Independent predictors of mortality and ICU admission were identified by means of backward stepwise logistic regression and described in terms of odds ratio (OR) and 95% confidence interval (95%CI). Results: A total of 883 patients were included, 51.8% men with a mean age of 68; 1.8% readmissions. 17.6% of patients died (n=154). The independent predictors of mortality were age (OR=1.071; 95%CI: 1.046-1.095), percentage of oxygen saturation (SatO2) (OR=0.938; 95%CI: 0.903-0.974), diastolic blood pressure (DBP, OR= 0.972; 95%CI: 0.955-0.989), creatinine (OR=1.516; 95%CI: 1.088-2.113), INR (OR=1.199; 95%CI: 1.012-1.419) and sodium (OR=1.082; 95%CI: 1.037-1.128). Eight percent of patients were admitted to ICU; the independent predictors were: male sex (OR=2.079; 95%CI: 1.099-3.935), age (OR=0.960; 95%CI: 0.942-0.979), SatO2 (OR=0.925; 95%CI: 0.889-0.962), creatinine (OR=1.551; 95%CI: 1.118-2.152) and C-reactiveprotein (CRP, OR=1.003; 95%CI: 1.000-1.007). Conclusion: The identification of independent predictors of mortality (age, SatO2, DBP, creatinine, INR, sodium) and ICU admission (sex, age, SatO2, creatinine, and CRP) allowed for the stratification of patients to adapt clinical care protocols to these findings, thereby improving medical decisions.(AU)

[What risk factors are associated with mortality and readmissions in osteoporotic hip fracture?] / ¿Qué factores de riesgo se asocian con la mortalidad y los reingresos en la fractura de cadera osteoporótica?

INTRODUCTION AND OBJECTIVE: Hip fracture in the elderly leads to long hospital stays, readmissions and mortality. OBJECTIVE: To identify risk factors associated with mortality and readmissions in elderly with hip fracture. PATIENTS AND METHODS: Prospective observational study in people over 65years with hip fracture between October-2017 and November-2018, followed for 12months (128 patients). STATISTICAL ANALYSIS: SPSS vs27.0. RESULTS: 6 (4.7%) patients were readmitted at 1 month; at year 24 (19.4%); 55 (44.4%) consulted for emergencies; 4 (3.1%) died during admission, and 26 (20.3%) in 12months; hospital stay 6.5 (SD: 4.80) days. Those with a previous Barthel less than 85 (6 [8.5%] vs 0 [0%]; P=.037) and less EuroQol5D (6 [10.0] vs 0 [0%]; P=.011) were readmitted more at one month. Those taking anticoagulants (OR: 3.33 (1.13-9.81); P=.003) and those with high surgical risk (18 [23.4%] vs 1 [5.6%]) were readmitted more after one year; P=.038). There was higher intra-episode mortality with renal failure (OR: 34.2 [3.25-359.93]; P=.003) and decompensated heart failure (OR: 23.8 [2.76-205.25]; P=.015). Higher mortality at one year in those older than 85years (OR: 4.3 [1.48-12.49]; P=.007); in those taking benzodiazepines (OR: 2.86 [1.06-7.73]; P=.038); if Barthel was less than 85 (OR: 2.96 [1.1-7.99]; P=.027) and if EuroQol5D was low (0.249 vs 0.547; P=.025). Those operated after 72h (24 [57.1%] vs. 29 [38.2%]; P=.047) consulted more for the emergency department. CONCLUSIONS: Renal failure and cardiac decompensation increased intra-episode mortality. Older age, benzodiazepines, and previous low functionality and low EuroQol5D increased mortality at one year. They were readmitted more if higher surgical risk, previously anticoagulated and worse quality of life and functionality.

A pilot study to estimate incidence of guanidinoacetate methyltransferase deficiency in newborns by direct sequencing of the GAMT gene.

BACKGROUND: GAMT deficiency is an autosomal recessive disorder of creatine biosynthesis causing developmental delays or intellectual disability in untreated patients as a result of irreversible brain damage occurring prior to diagnosis. Normal neurodevelopmental outcome has been reported in patients treated from neonatal period highlighting the importance of early treatment. METHODS: Five hundred anonymized newborns from the National Newborn Screening Program of The Netherlands were included into this pilot study. Direct sequencing of the coding region of the GAMT gene was applied following DNA extraction. The disease causing nature of novel missense variants in the GAMT gene was studied by overexpression studies. GAA and creatine was measured in blood dot spots. RESULTS: We detected two carriers, one with a known common (c.327G>A) and one with a novel mutation (c.297_309dup (p.Arg105Glyfs*) in the GAMT gene. The estimated incidence of GAMT deficiency was 1:250,000. We also detected five novel missense variants. Overexpression of these variants in GAMT deficient fibroblasts did restore GAMT activity and thus all were considered rare, but not disease causing variants including the c.131G>T (p.Arg44Leu) variant. Interestingly, this variant was predicted to be pathogenic by in silico analysis. The variants were included in the Leiden Open Variation Database (LOVD) database (www.LOVD.nl/GAMT). The average GAA level was 1.14µmol/L±0.45 standard deviations. The average creatine level was 408µmol/L±106. The average GAA/creatine ratio was 2.94±0.136. CONCLUSION: The estimated incidence of GAMT deficiency is 1:250,000 newborns based on our pilot study. The newborn screening for GAMT deficiency should be implemented to identify patients at the asymptomatic stage to achieve normal neurodevelopmental outcome for this treatable neurometabolic disease. Biochemical investigations including GAA, creatine and GAMT enzyme activity measurements are essential to confirm the diagnosis of GAMT deficiency. According to availability, all missense variants can be assessed functionally, as in silico prediction analysis of missense variants is not sufficient to confirm the pathogenicity of missense variants.